Senior Data Scientist - ML Leader for Fraud & Doc AI

Fnb Online; Pittsburgh (Allegheny County); On-site; USD 130,000 - 180,000; Full time

Job summary

F.N.B. Corporation's Strategy and Innovation team in Pittsburgh is seeking a Senior Data Scientist to lead the development and deployment of ML solutions across fraud detection, customer analytics, and document intelligence.

You will partner with senior leaders to translate business needs into scalable models, architect production ML systems, govern models with monitoring and drift detection, and deliver measurable business impact.

Qualifications

• BA or BS required with 5+ years of data science experience.
• Strong communication and stakeholder management.
• Expert in Python (pandas, scikit-learn) and SQL.
• Experience with ML model deployment and governance.
• Knowledge of NLP/ document intelligence is a plus.

Responsibilities

• Lead design and development of ML models for fraud detection, customer analytics, document intelligence, and forecasting.
• Partner with leaders to translate business needs into data-driven solutions.
• Architect end-to-end production ML systems with data pipelines and monitoring.
• Mentor junior data scientists and ensure modeling quality and governance.
• Communicate complex findings to technical and non-technical audiences; drive decision making.
• Design experiments to measure business impact and drive innovation across tools and methodologies.
• Collaborate with data engineering and IT to ensure successful implementation.

Skills

Python

SQL

Machine Learning

Statistical Modeling

Data Wrangling

Excel

PowerPoint

Communication

Project Management

Education

BA or BS

Tools

Python

Job description

F.N.B. Corporation's Strategy and Innovation team in Pittsburgh is seeking a Senior Data Scientist to lead the development and deployment of ML solutions across fraud detection, customer analytics, and document intelligence.

You will partner with senior leaders to translate business needs into scalable models, architect production ML systems, govern models with monitoring and drift detection, and deliver measurable business impact.